DocumentCode
445515
Title
Statistical optimisation and tuning of GA factors
Author
Petrovski, Andrei ; Brownlee, Alexander ; McCall, John
Author_Institution
Sch. of Comput., Robert Gordon Univ., Aberdeen
Volume
1
fYear
2005
fDate
5-5 Sept. 2005
Firstpage
758
Abstract
This paper presents a practical methodology of improving the efficiency of genetic algorithms through tuning the factors significantly affecting GA performance. This methodology is based on the methods of statistical inference and has been successfully applied to both binary-and integer-encoded genetic algorithms that search for good chemotherapeutic schedules
Keywords
cancer; drugs; genetic algorithms; inference mechanisms; patient treatment; statistical analysis; GA factors; binary-and integer-encoded; chemotherapeutic schedules; genetic algorithm; statistical inference; statistical optimization; Algorithm design and analysis; Analysis of variance; Application software; Computer science; Encoding; Genetic algorithms; Genetic engineering; Performance analysis; Processor scheduling; Space exploration;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Conference_Location
Edinburgh, Scotland
Print_ISBN
0-7803-9363-5
Type
conf
DOI
10.1109/CEC.2005.1554759
Filename
1554759
Link To Document